Processes and systems for achieving and assisting in improved nutrition based on food energy data and relative healthfulness data

ABSTRACT

Processes are provided for controlling body weight of a consumer, as well as for selecting and purchasing foods, and for producing food products, based on a combination of food energy data and relative healthfulness data for a candidate food. Various ways are provided for obtaining and accessing the food energy data and relative healthfulness data. Related processes and systems are also provided for assisting in the foregoing processes.

BENEFIT AND RELATED APPLICATIONS

This application claims the benefit of U.S. provisional patentapplication No. 61/092,981, filed Aug. 29, 2008, in the names of KarenMiller-Kovach, Ute Gerwig, Julia Peetz, Christine Jacobsohn, WanemaFrye, Stephanie Lyn Rost and Maria Kinirons. The present application isrelated to US patent application No. ______, entitled Processes andSystems Based on Metabolic Conversion Efficiency (Attorney docket No.26753.006); US patent application No. ______ entitled Processes andSystems Based on Dietary Fiber as Energy (Attorney docket No.26753.008); U.S. patent application Ser. No. ______, entitled Processesand Systems Using and Producing Food Healthfulness Data based on FoodMetagroups (Attorney docket No. 26753.010); U.S. patent application Ser.No. ______, entitled Processes and Systems Using and Producing FoodHealthfulness Data based on Linear Combinations of Nutrients (Attorneydocket No. 26753.012); and US patent application No. entitled Processesand Systems for Achieving and Assisting in Improved Nutrition (Attorneydocket No. 26753.014), each of which is filed concurrently herewith andall of which are hereby incorporated herein by reference in theirentireties.

FIELD OF THE INVENTION

Processes are provided for selecting, ingesting and/or purchasing foodsfor achieving weight control and/or healthful nutrition, as well asprocesses for producing food products, and systems for assisting witheach of the foregoing.

Background Of The Invention

Weight Watchers International, Inc. is the world's leading provider ofweight management services, operating globally through a network ofCompany-owned and franchise operations. Weight Watchers provides a widerange of products, publications and programs for those interested inweight loss and weight control. With over four decades of weightmanagement experience, expertise and know-how, Weight Watchers hasbecome one of the most recognized and trusted brand names among weightconscious consumers.

Years ago, Weight Watchers pioneered innovative and successful methodsfor weight control and systems for assisting consumers in practicingsuch methods. Such methods and systems are the subjects of U.S. Pat.Nos. 6,040,531; 6,436,036; 6,663,564; 6,878,885 and 7,361,143, each ofwhich is incorporated herein by reference in its entirety. These methodsassign values to food servings based on their calorie content, which isincreased on the basis of fat content and decreased on the basis ofdietary fiber content. This assignment is carried out using aproprietary formula developed by Weight Watchers scientists. The valuesfor food servings consumed each day are summed and the consumer ensuresthat they do not exceed a predetermined maximum value. These methodsafford a simple and effective weight control framework, especially forthose who cannot devote substantial attention to their weight controlefforts.

While the existing Weight Watchers® program has provided consumers witheffective techniques that have assisted millions in their efforts tolose excess body weight using its proprietary formula, consumers havelong expressed a desire that the formula reflect the relative satiety ofdifferent foods. Unfortunately, until now it has not been possible toquantify the aspect of satiety so that it could be incorporated in sucha formula.

While consumers are striving to control their body weight, whether forthe object of losing or gaining weight, or simply to maintain the weightthey have, they are also eager to ensure that they are eatinghealthfully. Both government and private entities are attempting toimplement measures to educate consumers so that they might chose andconsume healthier foods. In the United States of America (US), foodproducts are required to display lists of ingredients and provideadditional information such as the content of each macronutrient, totalcalories and content of nutrients such as sodium and saturated fat thatare particularly important to those with cardiovascular diseases.

The Food Standards Agency of the United Kingdom has implemented a foodlabeling system termed the “Traffic Light Labeling” system thatencourages food manufacturers to label their foods in a standard fashionto enable consumers to compare one product against another by comparingthe amounts of four different nutrients in each, including fat,saturated fat or “saturates”, sugar and salt, and, in some cases,calorie content. For each nutrient, and the calorie content (ifdisplayed), a color code is provided to indicate whether the amount ofthat nutrient is “high” (red color code), “medium” (amber color code) or“low” (green color code). For those keeping track of one or moreparticular nutrients, such as sodium and saturated fat in the case ofthose with a cardiovascular condition, this labeling system can be quiteeffective. But for those trying to develop an overall sense of thehealthfulness of each food product they are considering for purchaseand/or consumption, a considerable amount of judgment may be necessaryto determine whether to purchase or consume a particular food product.

Published PCT application WO 98/45766 to Sanchez proposes a food groupnutritional value calculator that inputs data such as that displayed infollowing the Traffic Light Labeling system along with a consumersselection of one of eight “food groups”. Based on the food groupselection, the calculator carries out a corresponding decision-treealgorithm by comparing the input amounts of selected nutrients againststandard values specific to each of the separate food groups. Based onone or more such comparisons, the food is classified as either“Excellent”, “Very Good”, “Good” or “Avoid”.

DISCLOSURE

FIGS. 1-9 are tables of data used in processes disclosed herein forproducing data representing the relative healthfulness of various foods;

FIG. 10 is a flow chart illustrating a process for controlling bodyweight in a human being in accordance with certain embodiments;

FIG. 11 is a flow chart illustrating certain disclosed processes forselecting and purchasing foods based on their food energy data andrelative healthfulness data;

FIG. 12 illustrates certain embodiments of a data processing systemuseful in the processes disclosed herein;

FIG. 13 illustrates a client/server system useful in the processesdisclosed herein;

FIG. 14 is a flowchart illustrating certain disclosed processes forweight control and selecting foods to be consumed based on datarepresenting their energy content and a desired nutritionalcharacteristic;

FIGS. 15A through 15D illustrate exemplary images for use in conveyingenergy content data and nutritional characteristic data of foods;

FIG. 16 is a flow chart illustrating a process for selecting andpurchasing foods based on their energy content and a desired nutritionalcharacteristic;

FIG. 17 is a flow chart used to illustrate certain embodiments of aprocess for producing a food product having an integrated imageassociated therewith.

For this application the following terms and definitions shall apply:

The term “energy content” as used herein refers to the energy content ofa given food, whether or not adjusted for the metabolic conversionefficiency of one or more nutrients in the food.

The term “metabolic conversion efficiency” as used herein includes bothabsolute measures of metabolic conversion efficiency and the metabolicconversion efficiency of nutrients relative to each other.

The term “data” as used herein means any indicia, signals, marks,symbols, domains, symbol sets, representations, and any other physicalform or forms representing information, whether permanent or temporary,whether visible, audible, acoustic, electric, magnetic, electromagneticor otherwise manifested. The term “data” as used to representpredetermined information in one physical form shall be deemed toencompass any and all representations of corresponding information in adifferent physical form or forms.

The term “presentation data” as used herein means data to be presentedto a user in any perceptible form, including but not limited to, visualform and aural form. Examples of presentation data include datadisplayed on a visual presentation device, such as a monitor, and dataprinted on paper.

The term “presentation device” as used herein means a device or devicescapable of presenting data to a user in any perceptible form.

The term “database” as used herein means an organized body of relateddata, regardless of the manner in which the data or the organized bodythereof is represented. For example, the organized body of related datamay be in the form of one or more of a table, a map, a grid, a packet, adatagram, a frame, a file, an e-mail, a message, a document, a list orin any other form.

The term “image dataset” as used herein means a database suitable foruse as presentation data or for use in producing presentation data.

The term “auxiliary image feature” as used herein means one or more ofthe color, brightness, shading, shape or texture of an image.

The term “network” as used herein includes both networks andinternetworks of all kinds, including the Internet, and is not limitedto any particular network or inter-network. For example, “network”includes those that are implemented using wired links, wireless links orany combination of wired and wireless links.

The terms “first”, “second”, “primary” and “secondary” are used todistinguish one element, set, data, object, step, process, activity orthing from another, and are not used to designate relative position orarrangement in time, unless otherwise stated explicitly.

The terms “coupled”, “coupled to”, and “coupled with” as used hereineach mean a relationship between or among two or more devices,apparatus, files, circuits, elements, functions, operations, processes,programs, media, components, networks, systems, subsystems, and/ormeans, constituting any one or more of (a) a connection, whether director through one or more other devices, apparatus, files, circuits,elements, functions, operations, processes, programs, media, components,networks, systems, subsystems, or means, (b) a communicationrelationship, whether direct or through one or more other devices,apparatus, files, circuits, elements, functions, operations, processes,programs, media, components, networks, systems, subsystems, or means,and/or (c) a functional relationship in which the operation of any oneor more devices, apparatus, files, circuits, elements, functions,operations, processes, programs, media, components, networks, systems,subsystems, or means depends, in whole or in part, on the operation ofany one or more others thereof.

The terms “communicate,” “communicating” and “communication” as usedherein include both conveying data from a source to a destination, anddelivering data to a communication medium, system, channel, network,device, wire, cable, fiber, circuit and/or link to be conveyed to adestination. The term “communications” as used herein includes one ormore of a communication medium, system, channel, network, device, wire,cable, fiber, circuit and link.

The term “processor” as used herein means processing devices, apparatus,programs, circuits, components, systems and subsystems, whetherimplemented in hardware, software or both, and whether or notprogrammable. The term “processor” as used herein includes, but is notlimited to one or more computers, hardwired circuits, neural networks,signal modifying devices and systems, devices and machines forcontrolling systems, central processing units, programmable devices andsystems, field programmable gate arrays, application specific integratedcircuits, systems on a chip, systems comprised of discrete elementsand/or circuits, state machines, virtual machines, data processors,processing facilities and combinations of any of the foregoing.

The term “data processing system” as used herein means a systemimplemented at least in part by hardware and comprising a data inputdevice, a data output device and a processor coupled with the data inputdevice to receive data therefrom and coupled with the output device toprovide processed data thereto.

The terms “obtain”, “obtained” and “obtaining”, as used with respect toa processor or data processing system mean (a) producing data byprocessing data, (b) retrieving data from storage, or (c) requesting andreceiving data from a further data processing system.

The terms “storage” and “data storage” as used herein mean one or moredata storage devices, apparatus, programs, circuits, components,systems, subsystems, locations and storage media serving to retain data,whether on a temporary or permanent basis, and to provide such retaineddata.

The terms “food serving identification data” and “food serving ID data”as used herein mean data of any kind that is sufficient to identify afood and to convey an amount thereof, whether by mass, weight, volume,or size, or by reference to a standard or otherwise defined foodserving, or by amounts of constituents thereof. The terms “amount” and“amounts” as used herein refer both to absolute and relative measures.

The terms “food identification data” and “food ID data” as used hereinmean data of any kind that is sufficient to identify a food, whether ornot such data conveys an amount thereof.

A process for controlling body weight of a consumer comprises, for eachof a plurality of candidate food servings, supplying at least one ofrespective food serving identification data and respective food servingnutrient data; obtaining respective food energy data representing anenergy content of each of the candidate food servings and respectivehealthfulness data representing a relative healthfulness of each of thecandidate food servings based on its at least one of respective foodserving identification data and respective food serving nutrient data;selecting food servings from the plurality of candidate food servingsbased on its respective healthfulness data and its respective foodenergy data such that a sum of respective food energy data of theselected food servings bears a predetermined relationship to apredetermined food energy benchmark for the consumer in a given period;and ingesting the selected food servings.

In certain embodiments, meal plan data comprising data identifyingcandidate food servings to be ingested by the consumer over the givenperiod is obtained based on the respective healthfulness data, therespective food energy data and the food energy benchmark, and thecandidate food servings are ingested by the consumer in accordance withthe meal plan data.

In certain embodiments, the respective healthfulness data for at leastone of the candidate food servings is based on (a) a selected respectiveprocedure for processing nutritional data of foods in a respective foodgroup comprising the at least one of the candidate food servings, therespective food group being one of a plurality of food groups of arespective metagroup of a plurality of metagroups, each of themetagroups comprising a plurality of food groups and having a differentrespective procedure for processing the nutritional data of foods in thefood groups within such metagroup, and (b) selected respectivecomparison data for the corresponding food group, at least some of thefood groups in each metagroup having different respective comparisondata than the other food groups in such metagroup. In certainembodiments, the respective healthfulness data representing a relativehealthfulness of each of the candidate food servings is based on alinear combination of selected nutrient amounts present therein.

In certain embodiments, the respective food energy data representing anenergy content of each of the candidate food servings is based on ahuman being's metabolic efficiency in utilizing first and secondnutrients therein as energy. In certain embodiments, the respective foodenergy data representing an energy content of each of the candidate foodservings is based on an energy contribution of each of its proteincontent, its carbohydrate content, its dietary fiber content and its fatcontent.

A process for selecting and purchasing food comprises, using at leastone of food identification data and food serving nutrient data of a foodoffered for sale, obtaining food energy data representing an energycontent thereof and relative healthfulness data representing a relativehealthfulness thereof; selecting the food offered for sale based on itsfood energy data and its relative healthfulness data; and purchasing theselected food offered for sale.

In certain embodiments, the relative healthfulness data of the foodoffered for sale is based on (a) a selected respective procedure forprocessing nutritional data of foods in a respective food groupcomprising the food offered for sale, the respective food group beingone of a plurality of food groups of a respective metagroup of aplurality of metagroups, each of the metagroups comprising a pluralityof food groups and having a different respective procedure forprocessing the nutritional data of foods in the food groups within suchmetagroup, and (b) selected respective comparison data for thecorresponding food group, at least some of the food groups in eachmetagroup having different respective comparison data than the otherfood groups in such metagroup. In certain embodiments, the relativehealthfulness data of the food offered for sale is based on a linearcombination of selected nutrient amounts present therein.

In certain embodiments, the food energy data representing an energycontent of the food offered for sale is based on a human being'smetabolic efficiency in utilizing first and second nutrients therein asenergy. In certain embodiments, the food energy data representing anenergy content of the food offered for sale is based on an energycontribution of each of its protein content, its carbohydrate content,its dietary fiber content and its fat content.

A process for providing data to a consumer to assist in a process forcontrolling the consumer's weight comprises receiving in a dataprocessing system data provided by a consumer for a food servingselected by the consumer including at least one of food servingidentification data and food serving nutrient data; using a processor ofthe data processing system, obtaining food energy data and foodhealthfulness data based on the at least one of food servingidentification data and food serving nutrient data; and at least one of(a) communicating the food energy data and the food healthfulness datato a device for presentation to the consumer, and (b) presenting thefood energy data and the food healthfulness data to the consumer via apresentation device of the data processing system.

In certain embodiments, the food healthfulness data is based on (a) aselected respective procedure for processing nutritional data of foodsin a respective food group comprising the food serving, the respectivefood group being one of a plurality of food groups of a respectivemetagroup of a plurality of metagroups, each of the metagroupscomprising a plurality of food groups and having a different respectiveprocedure for processing the nutritional data of foods in the foodgroups within such metagroup, and (b) selected respective comparisondata for the corresponding food group, at least some of the food groupsin each metagroup having different respective comparison data than otherfood groups in such metagroup. In certain embodiments, the foodhealthfulness data is based on a linear combination of selected nutrientamounts present in the food serving.

In certain embodiments, the respective food energy data is based on ahuman being's metabolic efficiency in utilizing first and secondnutrients in the food serving as energy. In certain embodiments, therespective food energy data of the food serving is based on an energycontribution of each of its protein content, its carbohydrate content,its dietary fiber content and its fat content.

A system for providing data to a consumer to assist in a process forcontrolling the consumer's weight comprises an input operative toreceive data provided by a consumer for a food serving selected by theconsumer including at least one of food serving identification data andfood serving nutrient data; a processor coupled with the input toreceive the data provided by the consumer and configured to obtain foodenergy data and food healthfulness data based on the at least one offood serving identification data and food serving nutrient data; and atleast one of (a) communications coupled with the processor to receivethe food energy data and the food healthfulness data therefrom and tocommunicate the food energy data and the food healthfulness data to adevice for presentation to the consumer, and (b) a presentation devicecoupled with the processor to receive the food energy data and the foodhealthfulness data and operative to present the food energy data and thefood healthfulness data to the consumer.

In certain embodiments, the processor is configured to obtain the foodhealthfulness data based on (a) a selected respective procedure forprocessing nutritional data of foods in a respective food groupcomprising the food serving, the respective food group being one of aplurality of food groups of a respective metagroup of a plurality ofmetagroups, each of the metagroups comprising a plurality of food groupsand having a different respective procedure for processing thenutritional data of foods in the food groups within such metagroup, and(b) selected respective comparison data for the corresponding foodgroup, at least some of the food groups in each metagroup havingdifferent respective comparison data than the other food groups in suchmetagroup. In certain embodiments, the processor is configured to obtainthe food healthfulness data based on a linear combination of selectednutrient amounts present in the food serving.

In certain embodiments, the processor is configured to obtain the foodenergy data based on a human being's metabolic efficiency in utilizingfirst and second nutrients in the food serving as energy. In certainembodiments, the processor is configured to obtain the food energy dataof the food serving based on an energy contribution of each of itsprotein content, its carbohydrate content, its dietary fiber content andits fat content.

A process for providing meal plan data to a consumer, comprisesreceiving request data in a data processing system representing arequest for a meal plan from a consumer; in response to the request,obtaining meal plan data in the data processing system representing aplurality of predetermined food servings to be consumed by the consumerduring a predetermined period based on food energy data and relativehealthfulness data for each thereof; and at least one of (a)communicating the meal plan data to a device for presentation to thedata requester, and (b) presenting the meal plan data to the datarequester via a presentation device of the data processing system.

In certain embodiments, the food energy data of at least one of theplurality of predetermined food servings is based on a human being'smetabolic efficiency in utilizing first and second nutrients therein asenergy. In certain embodiments, the food energy data of at least one ofthe plurality of predetermined food servings is based on an energycontribution of each of its protein content, its carbohydrate content,its dietary fiber content and its fat content.

In certain embodiments, the relative healthfulness data of at least oneof the plurality of predetermined food servings is based on (a) aselected respective procedure for processing nutritional data of foodsin a respective food group comprising the at least one of the pluralityof predetermined food servings, the respective food group being one of aplurality of food groups of a respective metagroup of a plurality ofmetagroups, each of the metagroups comprising a plurality of food groupsand having a different respective procedure for processing thenutritional data of foods in the food groups within such metagroup, and(b) selected respective comparison data for the corresponding foodgroup, at least some of the food groups in each metagroup havingdifferent respective comparison data than other food groups in suchmetagroup. In certain embodiments, the relative healthfulness data of atleast one of the plurality of predetermined food servings is based on alinear combination of selected nutrient amounts present in the at leastone of the plurality of predetermined food servings.

A system for providing meal plan data to a consumer comprises an inputoperative to receive request data representing a request for a meal planfrom the consumer; a processor coupled with the input to receive therequest data and configured to obtain meal plan data representing aplurality of predetermined food servings to be consumed by the consumerduring a predetermined period based on food energy data and relativehealthfulness data therefor; and at least one of (a) communicationscoupled with the processor to receive the meal plan data therefrom andto communicate the meal plan data to a device for presentation to theconsumer, and (b) a presentation device coupled with the processor toreceive the meal plan data and operative to present the meal plan datato the consumer.

In certain embodiments, the processor is configured to obtain therelative healthfulness data of at least one of the plurality ofpredetermined food servings based on (a) a selected respective procedurefor processing nutritional data of foods in a respective food groupcomprising the at least one of the plurality of predetermined foodservings, the respective food group being one of a plurality of foodgroups of a respective metagroup of a plurality of metagroups, each ofthe metagroups comprising a plurality of food groups and having adifferent respective procedure for processing the nutritional data offoods in the food groups within such metagroup, and (b) selectedrespective comparison data for the corresponding food group, at leastsome of the food groups in each metagroup having different respectivecomparison data than other food groups in such metagroup. In certainembodiments, the processor is configured to obtain the relativehealthfulness data of at least one of the plurality of predeterminedfood servings based on a linear combination of selected nutrient amountspresent therein.

In certain embodiments, the processor is configured to obtain the foodenergy data of at least one of the plurality of predetermined foodservings based on a human being's metabolic efficiency in utilizingfirst and second nutrients therein. In certain embodiments, theprocessor is configured to obtain the food energy data of at least oneof the plurality of predetermined food servings based on an energycontribution of each of its protein content, its carbohydrate content,its dietary fiber content and its fat content.

A process for producing a food product having food energy data andrelative healthfulness data associated therewith comprises, obtaining afood product, supplying at least one of food identification data andfood nutrient data of the food product; obtaining food energy data andrelative healthfulness data for the food product based on the at leastone of food identification data and food nutrient data of the foodproduct; and associating the food energy data and the relativehealthfulness data with the food product.

In certain embodiments, the food energy data and the relativehealthfulness data is associated with the food product by including thefood energy data and the relative healthfulness data on a substrateassociated with the food product. In certain ones of such embodiments,the substrate comprises a package for the food product. In certain onesof such embodiments, the substrate comprises a label accompanying thefood product.

Food servings can be specified in various ways, and preferably in waysthat are meaningful to consumers according to their local diningcustoms. Food servings may be specified by weight, mass, size or volume,or according to customary j ways of consuming food in the relevantculture. For example, in the United States it is customary to usemeasures such as cups, quarts, teaspoons, tablespoons, ounces, pounds,or even a “pinch”, in Europe, it is more common to use units such asliters, deciliters, grams and kilograms. In China and Japan it is alsoappropriate to use a measure such as a standard mass or weight held bychopsticks when consuming food.

In certain embodiments, food energy data is produced based on proteinenergy data representing the protein energy content, carbohydrate energydata representing the carbohydrate energy content and fat energy datarepresenting the fat energy content, of a candidate food serving, byapplying respective weight data to weight each of the protein energydata, the carbohydrate energy data and the fat energy data, each of theweight data representing the relative metabolic conversion efficiency ofthe corresponding nutrient and forming the food energy data based on asum of the weighted protein energy data, the weighted carbohydrateenergy data and the weighted fat energy data. The data for the variousnutrients is provided either by the consumer or by another source basedon data from the consumer, such as food identification data. If theprotein energy data is represented as “PRO”, the carbohydrate energydata as “CHO” and the fat energy data as “FAT”, in certain ones of suchembodiments, the food energy data (represented as “FED”) is obtained byprocessing the data in the manner represented by the following equation:

FED=(Wpro×PRO)+(Wcho×CHO)+(Wfat×FAT)  (1),

where Wpro represents the respective weighting data for PRO, Wchorepresents the respective weighting data for CHO and Wfat represents therespective weighting data for FAT. In certain ones of such embodiments,Wpro is selected from the range 0.7≤Wpro≤0.8, Wcho is selected from therange 0.9≤Wcho≤0.95 and Wfat is selected from the range 0.97≤Wfat≤1.0.In certain ones of such embodiments, Wpro is substantially equal to 0.8,Wcho is substantially equal to 0.95 and Wfat is substantially equal to1.0. Various measures of energy can be employed, such as kilocalories(kcal) and kilojoules (kJ).

In certain embodiments, food energy data is produced based on proteindata representing the mass or weight of the protein content (representedas PROm), carbohydrate data representing the mass or weight of thecarbohydrate content (represented as CHOm) and fat data representing themass or weight of the fat content (represented as FATm), of a candidatefood serving. In such embodiments, the protein data, carbohydrate dataand fat data are converted to energy data in producing the food energydata, by processing the protein data, carbohydrate data and fat data inthe manner represented by the following equation:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×CHOm)+(Wfat×Cf×FATm)  (2),

where Cp is a conversion factor for converting PROm to data representingthe energy content of PROm, Cc is a conversion factor for convertingCHOm to data representing the energy content of CHOm, and Cf is aconversion factor for converting FATm to data representing the energycontent of FATm. For example where the food energy data is representedin kilocalories and PROm, CHOm and FATm are expressed in grams, Cp isselected as 4 kilocalories/gram, Cc is selected as 4 kilocalories/gramand Cf is selected as 9 kilocalories/gram. Mass and weight data can beexpressed in the alternative by units such as ounces and pounds.

In certain embodiments, food energy data is produced based on total foodenergy data representing the total energy content, protein energy datarepresenting the protein energy content, and dietary fiber energy datarepresenting the dietary fiber energy content, of a candidate foodserving. More specifically, the food energy data is produced byseparating data representing the protein energy content and the dietaryfiber energy content (if present) from the total food energy data toproduce reduced energy content data, applying respective weight data toweight each of the protein energy data and the dietary fiber energydata, each of the weight data representing the relative metabolicconversion efficiency of the corresponding nutrient and forming the foodenergy data based on a sum of the reduced energy content data, theweighted protein energy data, and the weighted dietary fiber energydata. The data for the various nutrients is provided either by theconsumer or by another source based on data from the consumer, such asfood identification data. If the total food energy data is representedas “TFE”, protein energy data is represented as “PRO” and the dietaryfiber energy data as “DF”, in certain ones of such embodiments where TFEincludes an energy component of DF (as in the case of foods labeledaccording to practices adopted in the US and in the Dominion of Canada(CA)), the food energy data is obtained by processing the data in themanner represented by the following equation:

FED=(TFE−PRO−DF)+(Wpro×PRO)+(Wdf×DF)  (3),

where Wpro represents the respective weighting data for PRO and Wdfrepresents the respective weighting data for DF. In certain ones of suchembodiments, Wpro is selected from the range 0.7≤Wpro≤0.8 and Wdf isselected from the range 0<Wdf≤0.5. In certain ones of such embodiments,Wpro is substantially equal to 0.8 and Wdf is substantially equal to0.25. Various measures of energy can be employed, such as kilocalories(kcal) and kilojoules (kJ).

For those instances where TFE does not include a dietary fiber component(as in the case of foods labeled according to practices adopted inAustralia (AU) and the countries of central Europe (CE)), the process ofequation (3) is modified to the following form:

FED=(TFE−PRO)+(Wpro×PRO)+(Wdf×DF)  (4).

In certain embodiments, food energy data is produced based both on thetotal food energy data, as well as on protein data representing the massor weight of the protein content (represented as PROm) and dietary fiberdata representing the mass or weight of the dietary fiber content(represented as DFm), of a candidate food serving. In such embodimentsand for foods labeled as in the US and CA, the protein data and dietaryfiber data are converted to energy data in producing the food energydata, by processing the total food energy data, the protein data anddietary fiber data in the manner represented by the following equation:

FED=[TFE−(Cp×PROm)−(Cdf×DFm)]+(Wpro×Cp×PROm)+(Wdf×Cdf×DFm)  (6),

where Cp is a conversion factor for converting PROm to data representingthe energy content of PROm and Cdf is a conversion factor for convertingDFm to data representing an energy content of DFm. For example where thefood energy data is represented in kilocalories and PROm and DFm areexpressed in grams, Cp is selected as 4 kilocalories/gram and Cdf isselected as 4 kilocalories/gram. Mass and weight data can be expressedin the alternative by units such as ounces and pounds.

For those instances where TFE does not include a dietary fiber component(as in the case of foods labeled according to practices adopted in AUand CE), the process of equation (5) is modified to the following form:

FED=[TFE−(Cp×PROm)]+(Wpro×Cp×PROm)+(Wdf×Cdf×DFm)  (6).

In certain embodiments, food energy data is produced based on proteindata representing the protein energy content of a candidate foodserving, carbohydrate data representing its carbohydrate energy content,fat data representing its fat energy content, and dietary fiber datarepresenting its dietary fiber energy content. This data is providedeither by the consumer or from another source based on data from theconsumer, such as food identification data. If the protein energy datais represented as “PRO”, the carbohydrate energy data as “CHO”, the fatenergy data as “FAT”, and the dietary fiber energy data as “DF”, incertain ones of such embodiments, the food energy data (represented as“FED”) is obtained by processing the data in the manner represented bythe following equation:

FED=PRO+CHO+FAT+DF  (7).

In certain ones of such embodiments, food energy data is produced basedon the protein energy data, the carbohydrate energy data, the fat energydata, and the dietary fiber energy data, of the candidate food serving,by applying respective weight data to weight each of the protein energydata, the carbohydrate energy data, the fat energy data and the dietaryfiber energy data representing its relative metabolic conversionefficiency and forming the food energy data based on a sum of theweighted protein energy data, the weighted carbohydrate energy data, theweighted fat energy data and the weighted dietary fiber energy data. IfWpro represents the respective weighting data for PRO, Wcho representsthe respective weighting data for CHO, Wfat represents the respectiveweighting data for FAT and Wdf represents the respective weighting datafor dietary fiber, in certain ones of such embodiments, the food energydata (represented as “FED”) is obtained by processing the data in themanner represented by the following equation:

FED=(Wpro×PRO)+(Wcho×CHO)+(Wfat×FAT)+(Wdf×DF)  (8).

In certain ones of such embodiments, Wpro is selected from the range0.7≤Wpro≤0.8, Wcho is selected from the range 0.9≤Wcho≤0.95, Wfat isselected from the range 0.97≤Wfat≤1.0 and Wdf is selected from the range0<Wdf≤0.5 In certain ones of such embodiments, Wpro is substantiallyequal to 0.8, Wcho is substantially equal to 0.95, Wfat is substantiallyequal to 1.0 and Wdf is substantially equal to 0.25.

In certain embodiments, food energy data is produced based on proteindata representing the mass or weight of the protein content (representedas PROm), carbohydrate data representing the mass or weight of thecarbohydrate content (represented as CHOm), fat data representing themass or weight of the fat content (represented as FATm) and dietaryfiber data representing the mass or weight of the dietary fiber content(represented as DFm), of a candidate food serving. In such embodiments,the protein data, carbohydrate data, fat data and dietary fiber data,are converted to energy data in producing the food energy data, byprocessing the protein data, carbohydrate data, fat data and dietaryfiber data in the manner represented by the following equation:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×CHOm)+(Wfat×Cf×FATm)+(Wdf×Cdf×DFm)  (9),

where Cp is a conversion factor for converting PROm to data representingan energy content of PROm, Cc is a conversion factor for converting CHOmto data representing an energy content of CHOm, Cf is a conversionfactor for converting FATm to data representing an energy content ofFATm and Cdf is a conversion factor for converting DFm to datarepresenting an energy content of DFm. For example where the food energydata is represented in kilocalories and PROm, CHOm, FATm and DFm areexpressed in grams, Cp is selected as 4 kilocalories/gram, Cc isselected as 4 kilocalories/gram, Cf is selected as 9 kilocalories/gramand Cdf is selected as 4 kilocalories/gram.

In the US and in CA, where food labeling standards include a foodproduct's dietary fiber in its total carbohydrate amount in grams(represented as “Total_CHOm” herein), food energy data may instead beproduced by processing the protein data, carbohydrate data, fat data anddietary fiber data in the manner represented by the following equation:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×[Total_CHOm−DFm])+(Wfat×Cf×FATm)+(Wdf×Cdf×DFm)  (10).

In certain embodiments, the food energy data is produced in a modifiedfashion in order to discourage consumption of foods having a highsaturated fat content, so that the food energy data (FED) is based bothon the relative metabolic conversion efficiency of selected nutrientsand weighting data that promotes consumption of relatively morehealthful foods. In such embodiments, and where (as in the US and CA)food labeling standards include a food product's saturated fat(represented as “Sat_FATm” herein) in its total amount of fat in grams(represented as “Total_FATm” herein), the food energy data is producedby processing the protein data, carbohydrate data, fat data, saturatedfat data and dietary fiber data in the manner represented by thefollowing equation:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×[Total_CHOm−DFm])+(Wdf×Cdf×DFm)+(Wfat×Cf×[Total_FATm−Sat_FATm])+(Wsfat×Cf×Sat_Fatm)  (11),

wherein Wsfat represents modified weighting data for Sat_FATm. Incertain ones of such embodiments, Wpro is selected from the range0.7≤Wpro≤0.8, Wcho is selected from the range 0.9≤Wcho≤0.95, Wfat isselected from the range 0.97≤Wfat≤1.0, Wdf is selected from the range0<Wdf≤0.5, and Wsfat is selected from the range 1.0≤Wsfat≤1.3. Inparticular ones of such embodiments, Wpro is substantially equal to 0.8,Wcho is substantially equal to 0.95, Wfat is substantially equal to 1.0,Wdf is substantially equal to 0.25 and Wsfat is substantially equal to1.3.

The relatively higher value assigned to Wsfat is based, in part, on thedesirability of discouraging consumption of saturated fat, due to theill-health effects associated with this nutrient. The higher ranges andvalues of Wpro and Wcho in the presently disclosed embodiments relativeto those employed in embodiments disclosed hereinabove, are useful forweight loss processes. That is, consumers engaged in a weight lossprocess by limiting their food energy consumption could, in some cases,be encouraged to eat foods higher in saturated fat if it is assigned arelatively higher weight than other nutrients, since this tends toreduce their overall food energy consumption. By assigning relativelyhigher ranges and values for Wpro and Wcho for use in processes thatalso weight saturated fat higher than unsaturated fat, the potential toencourage consumption of saturated fat is substantially reduced.Accordingly, the weights assigned to Wpro and Wcho in the presentlydisclosed embodiments are based both on the relative metabolicconversion efficiency of protein and carbohydrates and the desire topromote consumption of relatively more healthful foods.

In certain embodiments, for foods containing alcohol, the foregoingprocesses as represented by equation (11) are modified to add a termrepresenting an energy component represented by the amount of alcohol inthe food. Where the amount of alcohol (by weight or mass) is expressedin grams (represented as “ETOHm” herein), this term is produced bymultiplying ETOHm by a weighting factor Wetoh and a conversion factorCetoh, where Wetoh is selected from the range 1.0≤Wetoh≤1.3, and inparticular ones of such embodiments is substantially equal to 1.29, andCetoh is selected as 9 kilocalories/gram, based on the principle thatalcohol is metabolized in the same pathway as fat. The higher valueassigned to Wetoh is based, in part, on the desirability of discouragingconsumption of alcohol, due to the ill-health effects associated withthis nutrient. Where a food contains alcohol, in certain embodiments itsfood energy data is produced by processing PROm, Total_CHOm, DFm,Total_FATm, Sat_FATm, and ETOHm in the manner represented by thefollowing equation:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×[Total_CHOm−DFm])+(Wdf×Cdf×DFm)+(Wfat×Cf×[Total_FATm−Sat_FATm])+(Wsfat×Cf×Sat_Fatm)+(Wetoh×Cetoh×ETOHm)  (12).

The process represented by equation (12) is modified for use in CE andAU and is represented as follows:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×Total_CHOm)+(Wdf×Cdf×DFm)+(Wfat×Cf×[Total_FATm−Sat_FATm])+(Wsfat×Cf×Sat_Fatm)+(Wetoh×Cetoh×ETOHm)  (13).

In certain embodiments, for foods containing sugar alcohol, theforegoing processes as represented by equations (12) and (13) aremodified to add a term representing an energy component represented bythe amount of sugar alcohol in the food. Where the amount of sugaralcohol (by weight or mass) is expressed in grams (represented as“SETOHm” herein), this term is produced by multiplying SETOHm by aweighting factor Wsetoh and a conversion factor Csetoh, where Wsetoh isselected from the range 0.9≤Wsetoh≤0.95, and in particular ones of suchembodiments is substantially equal to 0.95, and Csetoh is selected fromthe range 0.2 to 4.0 kilocalories/gram, and in particular ones of suchembodiments is substantially equal to 2.4. Where a food contains sugaralcohol, in certain embodiments its food energy data is produced byprocessing PROm, Total_CHOm, DFm, Total_FATm, Sat_FATm, ETOHm and SETOHmin the manner represented by the following equation:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×[Total_CHOm−DFm−SETOHm])+(Wdf×Cdf×DFm)+(Wfat×Cf×[Total_FATm−Sat_FATm])+(Wsfat×Cf×Sat_Fatm)+(Wetoh×Cetoh×ETOHm)+(Wsetoh×Csetoh×SETOHm)  (14).

The process represented by equation (14) is modified for use in CE andAU and is represented as follows:

FED=(Wpro×Cp×PROm)+(Wcho×Cc×[Total_CHOm−SETOHm])+(Wdf×Cdf×DFm)+(Wfat×Cf×[Total_FATm−Sat_FATm])+(Wsfat×Cf×Sat_Fatm)+(Wetoh×Cetoh×ETOHm)+(Wsetoh×Csetoh×SETOHm)  (15).

For the consumer's convenience, in many applications (such as the WeightWatchers® program) the food energy data is converted to simplified wholenumber data for a candidate food serving by producing dietary dataexpressed as whole number data by dividing the food energy data byfactor data, such as data having a value of 35, and rounding theresulting value to produce the simplified whole number data. (Of course,to assign 35 as the value of the factor data is arbitrary, and any othervalue such as 50, 60 or 70 may be used for this purpose.)

In the manner described above, the consumer can easily track foodconsumption throughout a period, such as a day or a week, (eithermanually or with the assistance of a data processing system) to ensurethat a predetermined sum of the dietary data for the food consumed bearsa predetermined relationship to a value of predetermined whole numberbenchmark data based on one or more of the consumer's age, body weight,height, gender and activity level. For example, if the consumer isfollowing a weight loss program, the predetermined whole numberbenchmark data is set at a value selected to ensure that the consumerwill lose weight at a safe rate if he or she consumes an amount of foodduring the period having a sum of dietary data that does not exceed thepredetermined whole number benchmark data.

Since individual food energy needs vary with the individual's age,weight, gender, height and activity level, in certain embodiments thepredetermined whole number benchmark data is selected based on one ormore of these variables. In such embodiments, food energy needs areestimated based on methods published by the National Academies Press,Washington, DC, USA in Dietary Reference Intakes for Energy,Carbohydrates, Fiber, Fat, Fatty Acids, Cholesterol, Protein and AminoAcids, 2005, pages 203 and 204. More specifically, as explained thereinthese methods estimate that men aged 19 years and older have a totalenergy expenditure (TEE) determined as follows:

TEE=864−(9.72×age)+PA−(14.2×weight+503×height)  (16),

and that women aged 19 years and older have a TEE determined as follows:

TEE=387−(7.31×age)+PA×(10.9×weight+660.7×height)  (17),

where age is given in years, weight in kilograms and height in meters.

In such embodiments, these methods are employed on the basis that allindividuals have a “low active” activity level, so that the activitylevel (PA) for men is set at 1.12 and PA for women is set at 1.14. Thepublished methods assume a 10 percent conversion cost regardless of thetypes and amounts of nutrients consumed; consequently, TEE is adjustedby subtracting 10 percent of the calculated TEE. Also, the publishedmethod of calculating TEE assigns an energy content of zero to certainfoods having a non-zero energy content. The total energy content of suchfoods consumed within a given day generally falls within a range of 150to 250 kilocalories, which may be normalized as 200 kilocalories.Accordingly, TEE as determined by the published method is adjusted toproduce adjusted TEE (ATEE) in a process represented by the followingequation:

ATEE=TEE−(TEE×0.10)+200  (18),

where ATEE and TEE are given in kilocalories.

For consumers carrying out a process of reducing body weight, thepredetermined whole number benchmark is obtained by subtracting anamount from the adjusted TEE selected to ensure a predetermined weightloss over a predetermined period of time. For example, a safe weightloss process can be selected to produce a loss of two pounds per week,or a consumption of 1000 kilocalories per day less than ATEE for a givenindividual. In this example, to produce the predetermined whole numberbenchmark data (PWNB), where the factor data used to produce the dietarydata for the candidate food servings (whether having a value of 35, 50,60, 70 or other value) is represented as FAC, such data is produced by aprocess represented by the following equation:

PWNB=(ATEE−1000)+FAC  (19).

To achieve weight loss, the value of (ATEE− 1000) in certain embodimentsis selected to fall within a range of 1000 kilocalories to 2500kilocalories, so that if (ATEE− 1000) is less than 1000 kilocalories,then (ATEE is set equal to 1000 kilocalories, and if (ATEE− 1000) isgreater than 2500 kilocalories, (ATEE− 1000) is set equal to 2500kilocalories. However, in various other embodiments, the upper limit of2500 kilocalories varies from 2000 to 3000 kilocalories, and the lowerlimit of 1000 kilocalories varies from 500 to 1500 kilocalories.

In certain embodiments, the relative healthfulness data is determined ina manner that depends on a particular food group of the selected food.In certain ones of such embodiments, the healthfulness data isdetermined in a first, common manner for foods within a first metagroupcomprising the following groups: beans, dry & legumes; and oils. Thehealthfulness data (HD) for these groups is obtained based on a linearcombination of fat content data, saturated fat content data, sugarcontent data and sodium content data for the food. In one suchembodiment, the healthfulness data is produced by processing fat contentdata (F_data), saturated fat content data (SF_data), sugar content data(S_data) and sodium content data (NA_data), as follows, wherein suchdata is determined as explained hereinbelow:

HD=[(2×(SF_data+F_data)+S_data+NA_data]4/kcal_DV  (20)

where kcal_DV is determined as explained hereinbelow. The table of FIG.1 illustrates how the foods in these groups are ranked according totheir healthfulness based on their respective healthfulness dataproduced in accordance with the process represented by equation (20) anda comparison thereof against the exemplary comparison data includedtherein. These values may be varied from place to place, from culture toculture and from time to time, to provide a fair comparison of availablefoods and food products.

It will also be appreciated that the food groups and metagroups, and thecorresponding procedures and comparison values, as disclosed herein maybe varied based on variations in the foods and food products availablefrom place to place, culture to culture and over time. They may alsovary to accommodate the needs and desires of certain segments of thepopulation, such as those with special needs (for example, diabeticpatients and those living in extreme climates) and those with particularhealthfulness goals (which can vary, for example, with physical activitylevel). Such groups, metagroups, procedures, and comparison values areselected based on the similarities of foods and the manner in whichrelated foods vary in the amounts and types of nutrients that tend toaffect their healthfulness.

The value selected for kcal_DV is selected to represent a daily calorievalue that depends on the purposes or needs of the class of consumersfor whom the relative healthfulness data is provided. For example, ifthis class encompasses individuals desiring to loose body weight, thevalue of kcal_DV is selected as a daily calorie target to ensure weightloss, such as 1500 kcal. However, this value may differ from culture toculture and from country to country. For example, the energy needs ofthose living in China are generally lower than those living in theUnited States, so that kcal_DV may be selected at a lower value forChinese individuals trying to reduce body weight than for those livingin the United States. As a further example, if the class of consumersfor whom the relative healthfulness data is provided encompassesathletes attempting to maintain body weight during training, kcal_DV maybe set at a much higher level than 1500 kcal. For most purposes, kcal_DVmay be selected in a range from 1000 kcal to 3000 kcal.

The value of SF_data is determined relative to a recommended orotherwise standardized limit on an amount or proportion of saturated fatto be included in a person's daily food intake. The. recommended orotherwise standardized amount or proportion of saturated fat to beconsumed daily is based on the person's presumed total food energyintake daily, and a proportion thereof represented by saturated fat. Incertain embodiments, for consumers desiring to lose body weight, asexplained hereinabove, a total food energy intake of 1500 kcal isassumed (although the amount may vary in other embodiments). If, forexample, a maximum desirable percentage of saturated fat consumed as aproportion of total daily energy intake is assumed to be seven percent,then the total number of calories in saturated fat that the personconsumes daily on such a diet should be limited to about 105 kcal (of atotal of 1500 kcal). Since fat contains about nine kcal per gram, theperson's daily consumption of saturated fat in this example should belimited to about twelve grams. However, the recommended or standardizedlimit on the proportion or amount of saturated fat to be consumed mayvary from one class of consumer to another, as well as from country tocountry and from culture to culture. SF_data is determined by comparisonto such a standard. In this example, therefore, SF_data is determined asthe ratio of (a) the mass of saturated fat in a standard amount of thefood under evaluation, to (b) twelve grams. While a different procedureor other amounts or proportions may be employed in other embodiments toevaluate the saturated fat content of a food, it is desired to determineSF_data in a manner that is reasonably comparable to the ways in whichF_data, S_data and NA_data are determined.

Similarly to SF_data, the value of F_data is determined relative to arecommended or otherwise standardized limit on the amount or proportionof total fat to be included in a person's daily food intake. In thoseembodiments in which it is presumed that a person consumes 1500 kcaldaily and a recommended proportion or limit of thirty percent of energyconsumption in the form of fat is adopted, this translates to fiftygrams of total fat on a daily basis. In this example, therefore, and inparticular for comparability to SF_data, F_data is determined as theratio of (a) the mass of total fat in a standard amount of the foodunder evaluation, to (b) fifty grams. Of course, a different procedureor other amounts or proportions may be employed in other embodiments toevaluate the total fat content of a food.

In a similar manner, the value of S_data is determined relative to arecommended or otherwise standardized limit on the amount or proportionof sugar to be included in a person's daily food intake. In thoseembodiments in which it is presumed that a person consumes 1500 kcaldaily and a recommended proportion or limit of ten percent of foodenergy intake in the form of sugar is adopted, this translates to thirtyeight grams of sugar on a daily basis (at four kcal per gram of sugar).In this example, therefore, and in particular for comparability toSF_data and F_data, S_data is determined as the ratio of (a) the mass ofsugar in a standard amount of the food under evaluation, to (b) thirtyeight grams. Of course, a different procedure or other amounts orproportions may be employed in other embodiments to evaluate the sugarcontent of a food.

In a manner similar to those described above, the value of NA_data isdetermined relative to a recommended or otherwise standardized limit onthe amount or proportion of sodium to be included in a person's dailyfood intake. In those embodiments in which a recommended limit of 2400mg of sodium consumed daily is adopted, NA_data is determined as theratio of (a) the mass of sodium in a standard amount of the food underevaluation, to (b) 2400 mg. Of course, a different procedure or otheramounts or proportions may be employed in other embodiments to evaluatethe sodium content of a food.

In such embodiments, the healthfulness data is determined in a second,common manner for foods within a second metagroup comprising thefollowing groups: beef (cooked), cookies, cream & creamers, eggs,frankfurters, game (raw), game (cooked), lamb (cooked), luncheon meats,pizza, pork (raw), pork (cooked), sausage, snacks—pretzels, veal (raw)and veal (cooked). The healthfulness data (HD) for these groups isobtained based on a linear combination of the food's fat content data,saturated fat content data, sugar content data, sodium content data andenergy density data. In one such embodiment, the healthfulness data isproduced by processing F_data, SF_data, S_data, NA_data and ED_data ofthe food, as follows, wherein F_data, SF_data, S_data and NA_data areobtained as explained hereinabove:

HD=ED_data+([(2×SF_data)+(2×F_data)+NA_data+S_data]×100/M_serving)  (21),

where M_serving is the mass or weight of a standard serving of the food.In this particular embodiment, ED_data is obtained as the energy contentof the food (in kcal) divided by its mass (in grams). The tables ofFIGS. 1A and 1B illustrate how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(21) and a comparison thereof against the exemplary comparison dataincluded therein.

In such embodiments, the healthfulness data is determined in a third,common manner for foods within a third metagroup comprising thefollowing groups: beverages; alcoholic beverages; sweet spreads—jams,syrups, toppings & nut butters. The healthfulness data (HD) for thesegroups is obtained based on a linear combination of the food's fatcontent data, saturated fat content data, sugar content data, sodiumcontent data and energy density data. In one such embodiment, thehealthfulness data is produced by processing F_data, SF_data, S_data,NA_data, ED_data and M_serving, as follows:

HD=(ED_data+3)+[(2×SF_data)+(2×F_data)+(2×S_data)+NA_data]+M_serving  (22).

The table of FIG. 2 illustrates how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(22) and a comparison thereof against the exemplary comparison dataincluded therein.

In such embodiments, the healthfulness data is determined in a fourth,common manner for foods within a fourth metagroup comprising thefollowing groups: cheese, dairy & non-dairy, hard; and cheese, cottage &cream. The healthfulness data (HD) for these groups is obtained based ona linear combination of the food's fat content data, saturated fatcontent data, sugar content data, sodium content data and energy densitydata. In one such embodiment, the healthfulness data is produced byprocessing F_data, SF_data, S_data, NA_data, ED_data and M_serving, asfollows:

HD=ED_data+[(4×SF_data)+(4×F_data)+S_data+NA_data]×100/M_serving  (23).

The table of FIG. 2A illustrates how the foods in these groups areranked according to their healthfulness based on their respectivehealthfulness data produced in accordance with the process representedby equation (23) and a comparison thereof against the exemplarycomparison data included in FIG. 2A.

In such embodiments, the healthfulness data is determined in a fifth,common manner for foods within a fifth metagroup comprising thefollowing groups: breads; bagels; tortillas, wraps; breakfast—pancakes,waffles, pastries; and vegetable dishes The healthfulness data (HD) forthese groups is obtained based on a linear combination of the food's fatcontent data, saturated fat content data, sugar content data, sodiumcontent data and energy density data. In one such embodiment, thehealthfulness data is produced by processing F_data, SF_data, S_data,NA_data, ED_data and M_serving, as follows:

HD=ED_data+[(2×SF_data)+F_data+S_data+(2×NA_data)−DF_data]×100/M_serving  (24).

The value of DF_data is determined relative to a recommended orotherwise standardized minimum amount or proportion of dietary fiber tobe included in a person's daily food intake. One such recommendation isthat a minimum of ten grams of dietary fiber be consumed by a person forevery 1000 kcal consumed daily. In those embodiments in which it ispresumed that a person consumes 1500 kcal daily, this translates to arecommended minimum of fifteen grams of dietary fiber on a daily basis.Of course, a different procedure or other amounts or proportions may beemployed in other embodiments to evaluate the recommended amount ofdietary fiber to be consumed on a periodic basis. In this particularexample, the value of DF_data is obtained as the ratio of the mass ofdietary fiber in a standard serving of then food, to fifteen grams.

The table of FIG. 3 illustrates how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(24) and a comparison thereof against the exemplary comparison dataincluded in FIG. 3 .

In such embodiments, the healthfulness data is determined in a sixth,common manner for foods within a sixth metagroup comprising thefollowing groups: grains & pasta, cooked; and grains & pasta, uncooked.The healthfulness data (HD) for these groups is obtained based on alinear combination of the food's fat content data, saturated fat contentdata, sugar content data, sodium content data, energy density data anddietary fiber content data. In one such embodiment, the healthfulnessdata is produced by processing F_data, SF_data, S_data, NA_data, ED_dataand DF_data, as follows:

HD=(ED_data/3)+[([SF_data+F_data+(2×S_data)+(2×NA_data)]/4)−DF_data]×100/M_serving  (25).

The table of FIG. 3A illustrates how the foods of the groups in thesixth metagroup are ranked according to their healthfulness based ontheir respective healthfulness data produced in accordance with theprocess represented by equation (25) and a comparison thereof againstthe exemplary comparison data included in FIG. 3A.

In such embodiments, the healthfulness data is determined in a seventh,common manner for foods within a seventh metagroup comprising thefollowing groups: breakfast cereals, hot, cooked; breakfast cereals,hot, uncooked; and fruit salads. The healthfulness data (HD) for thesegroups is obtained based on a linear combination of the food's saturatedfat content data, fat content data, sugar content data, sodium contentdata and energy density data. In one such embodiment, the healthfulnessdata is produced by processing SF_data, F_data, S_data, NA_data andED_data, as follows:

HD=ED_data+[SF_data+(2×F_data)+(2×S_data)+(2×NA_data]×100/M_serving  (26).

The table of FIG. 4 illustrates how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(26) and a comparison thereof against the exemplary comparison dataincluded in FIG. 4 .

In such embodiments, the healthfulness data is determined in an eighth,common manner for foods within an eighth metagroup comprising thefollowing groups: bars; cakes and pastries; and candy. The healthfulnessdata (HD) for these groups is obtained based on a linear combination ofthe food's fat content data, saturated fat content data, sodium contentdata, energy density data and sugar content data. In one suchembodiment, the healthfulness data is produced by processing F_data,SF_data, NA_data, ED_data and S_data, as follows:

HD=ED_data+[(2×SF_data)+F_data+(2×S_data)+(2×NA_data)]×100/M_serving  (27).

The table of FIG. 5 illustrates how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(27) and a comparison thereof against the exemplary comparison dataincluded in FIG. 5 .

In such embodiments, the healthfulness data is determined in a ninth,common manner for foods within a ninth metagroup comprising thefollowing groups: dips; dressings; gravies; sauces; soups, condensed;soups, RTE; and spreads (other than sweet). The healthfulness data (HD)for these groups is obtained based on a linear combination of the food'sfat content data, saturated fat content data, sodium content data, sugarcontent data and energy density data. In one such embodiment, thehealthfulness data is produced by processing F_data, SF_data, S_data,NA_data, and ED_data, as follows:

HD=ED_data+[(2×SF_data)+F_data+S_data+(2×NA_data)]×100/M_serving  (28).

The table of FIG. 6 illustrates how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(28) and a comparison thereof against the exemplary comparison dataincluded in FIG. 6 .

In such embodiments, the healthfulness data is determined in a tenth,common manner for foods within a tenth metagroup comprising thefollowing groups: beans, dry & legumes dishes; beef dishes; breakfastmixed dishes; cheese dishes; chili, stew; egg dishes; fish & shellfishdishes; lamb dishes; pasta dishes; pasta, cooked; pork dishes; poultrydishes; rice & grains dishes; salads, main course; salads, side;sandwiches; veal dishes and vegetarian meat substitutes. Thehealthfulness data (HD) for these groups is obtained based on a linearcombination of the food's fat content data, saturated fat content data,sodium content data, sugar content data and energy density data. In onesuch embodiment, the healthfulness data is produced by processingF_data, SF_data, NA_data, S_data and ED_data, as follows:

HD=ED_data+[(2×SF_data)+(2×F_data)+S_data+(2×NA_data)]×100/M_serving  (29).

The tables of FIGS. 7 and 7A illustrate how the foods in these groupsare ranked according to their healthfulness based on their respectivehealthfulness data produced in accordance with the process representedby equation (29) and a comparison thereof against the exemplarycomparison data included in FIGS. 7 and 7A.

In such embodiments, the healthfulness data is determined in aneleventh, common manner for foods within an eleventh metagroupcomprising the following groups: fruit—fresh, frozen & dried; and fruit& vegetable juices. The healthfulness data (HD) for these groups isobtained based on a linear combination of the food's sodium contentdata, sugar content data, saturated fat content data, fat content dataand energy density data. In one such embodiment, the healthfulness datais produced by processing NA_data, S_data, SF_data, F_data and ED_data,as follows:

HD=ED_data+[(2×S_data)+NA_data+SF_data+F_data]×100/M_serving  (30).

The table of FIG. 8 illustrates how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(30) and a comparison thereof against the exemplary comparison dataincluded in FIG. 8 .

In such embodiments, the healthfulness data is determined in a twelfth,common manner for foods within a twelfth metagroup comprising thefollowing groups: vegetables, raw; and vegetables, cooked. Thehealthfulness data (HD) for these groups is obtained based on a linearcombination of the food's sodium content data, sugar content data,saturated fat content data, fat content data and energy density data. Inone such embodiment, the healthfulness data is produced by processingNA_data, S_data, SF_data, F_data and ED_data, as follows:

HD=ED_data+[S_data+(1.5×NA_data)+(5×SF_data)+(5×F_data)]×100/M_serving  (31).

The table of FIG. 8A illustrates how the foods in these groups areranked according to their healthfulness based on their respectivehealthfulness data produced in accordance with the process representedby equation (31) and a comparison thereof against the exemplarycomparison data included in FIG. 8A.

In such embodiments, the healthfulness data is determined in athirteenth, common manner for foods within a thirteenth metagroupcomprising the following groups: gelatin, puddings; ice cream desserts;ice cream novelties; ice cream, sherbet, sorbet; sweet pies; andsweets—honey, sugar, syrup, toppings. The healthfulness data (HD) forthese groups is obtained based on a linear combination of the food'ssodium content data, fat content data, saturated fat content data, sugarcontent data, and energy density data. In one such embodiment, thehealthfulness data is produced by processing NA_data, F_data, SF_data,S_data, and ED_data, as follows:

HD=ED_data+[(2×SF_data)+F_data+NA_data+(2×S_data)]×100/M_serving  (32).

The table of FIG. 9 illustrates how the foods in these groups are rankedaccording to their healthfulness based on their respective healthfulnessdata produced in accordance with the process represented by equation(32) and a comparison thereof against the exemplary comparison dataincluded in FIG. 9 .

In such embodiments, the healthfulness data is determined in afourteenth, common manner for foods within the following group:breakfast cereals, RTE. The healthfulness data (HD) for this group isobtained based on the saturated fat content data of the food, as well asits fat content data, sugar content data, sodium content data, dietaryfiber content data and energy density data. In one such embodiment, thehealthfulness data is produced by processing SF_data, F_data, S_data,NA_data, DF_data and ED_data, as follows:

HD=(ED_data/3)+[(2×S_data)+SF_data+F_data+NA_dataDF_data]×100/M_serving  (33).

For this group, the most healthful foods have an HD value less than orequal to −0.36, while less healthful foods have an HD value greater than−0.36 and less than or equal to 1.66, even less healthful foods have anHD value greater than 1.66 and less than or equal to 2.91 and the mostunhealthful foods have an HD value greater than 2.91.

In such embodiments, the healthfulness data is determined in afifteenth, common manner for foods within an fifteenth metagroupcomprising the following group: coffee/tea drinks with milk. Thehealthfulness data (HD) for this group is obtained based on thesaturated fat content data, the fat content data, the sodium contentdata and the sugar content data of the food. In one such embodiment, thehealthfulness data is produced by processing SF_data, F_data, S_data andNA_data, as follows:

HD=([(2×SF_data)+(2×F_data)+(2×S_data)+NA_data]/4)/kcal_DV  (34).

For this group, the most healthful foods have an HD value less than orequal to 3.25, while relatively less healthful foods have an HD valuegreater that 3.25 and less than or equal to 3.471, even less healthfulfoods have an HD value greater than 3.471 and less than or equal to 4.18and the least healthful foods have an HD value greater than 4.18.

In such embodiments, the healthfulness data is determined in asixteenth, common manner for foods within the following group: crackers.The healthfulness data (HD) for this group is obtained based on thesaturated fat content data, the fat content data, the sugar contentdata, the sodium content data and the energy density data of the food.In one such embodiment, the healthfulness data is produced by processingSF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=(ED_data/3)+[(2×SF_data)+F_data+S_data+(2×NA_data)]×100/M_serving  (35).

For this group, none of the foods are graded in the most healthful foodscategory, while relatively less healthful foods have an HD less than orequal to 1.805, even less healthful foods have an HD value greater than1.805 and less than or equal to 3.2, and the least healthful foods havean HD value greater than 3.2.

In such embodiments, the healthfulness data is determined in aseventeenth, common manner for foods within the following group: fish,cooked. The healthfulness data (HD) for this group is obtained based onthe saturated fat content data, the fat content data, the sugar contentdata, the sodium content data and the energy density data of the food.In one such embodiment, the healthfulness data is produced by processingSF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=ED_data+[(4×SF_data)+(4×F_data)+S_data+(2×NA_data)]×100/M_serving  (36).

For this group, the most healthful foods have an HD value less than orequal to 3.2, while relatively less healthful foods have an HD valuegreater that 3.2 and less than or equal to 4.7, even less healthfulfoods have an HD value greater than 4.7 and less than or equal to 6.6,and the least healthful foods have an HD value greater than 6.6.

In such embodiments, the healthfulness data is determined in aeighteenth, common manner for foods within the following group: fruit,canned. The healthfulness data (HD) for this group is obtained based onthe saturated fat content data, the fat content data, the sugar contentdata, the sodium content data and the energy density data of the food.In one such embodiment, the healthfulness data is produced by processingSF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=ED_data+[(2×SF_data)+(2×F_data)+(4×S_data)+(2×NA_data)]×100/M_serving  (37).

For this group, the most healthful foods have an HD value less than orequal to 1.56, while relatively less healthful foods have an HD valuegreater that 1.56 and less than or equal to 1.93, even less healthfulfoods have an HD value greater than 1.93 and less than or equal to 3.27,and the least healthful foods have an HD value greater than 3.27.

In such embodiments, the healthfulness data is determined in anineteenth, common manner for foods within the following group: nuts,nut butters. The healthfulness data (HD) for this group is obtainedbased on the saturated fat content data, the fat content data, the sugarcontent data, the sodium content data and the energy density data of thefood. In one such embodiment, the healthfulness data is produced byprocessing SF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=(ED_data/3)+[(2×SF_data)+F_data+S_data+NA_data]×100/M_serving  (38).

For this group, none of the foods are graded within the most healthfulfoods category, while relatively less healthful foods have an HD valueless than or equal to 1.5, even less healthful foods have an HD valuegreater than 1.5 and less than or equal to 5.6, and the least healthfulfoods have an HD value greater than 5.6.

In such embodiments, the healthfulness data is determined in atwentieth, common manner for foods within the following group: snacks,other. The healthfulness data (HD) for this group is obtained based onthe saturated fat content data, the fat content data and the energydensity data of the food. In one such embodiment, the healthfulness datais produced by processing SF_data, F_data and ED_data, as follows:

HD=ED_data+[SF_data+F_data]×100/M_serving  (39).

For this group, none of the foods are graded within the most healthfulfoods category or in the relatively less healthful foods category, whileeven less healthful foods have an HD value less than or equal to 5.491,and the least healthful foods have an HD value greater than 5.491.

In such embodiments, the healthfulness data is determined in atwenty-first, common manner for foods within the following group:snacks—popcorn. The healthfulness data (HD) for this group is obtainedbased on the saturated fat content data of the food, as well as its fatcontent data, sugar content data, sodium content data, dietary fibercontent data and energy density data. In one such embodiment, thehealthfulness data is produced by processing SF_data, F_data, S_data,NA_data, DF_data and ED_data, as follows:

HD=ED_data+[(2×S_data)+SF_data+F_data+NA_data-DF_data]×100/M_serving  (40).

For this group, the most healthful foods have an HD value less than orequal to 3.02, while less healthful foods have an HD value greater than3.02 and less than or equal to 4.0, even less healthful foods have an HDvalue greater than 4.0 and less than or equal to 6.3 and the mostunhealthful foods have an HD value greater than 6.3.

In certain embodiments, methods are provided for selecting and ingestingfoods in a way that enables the consumer to control body weight, whilesimplifying the task of evaluating the relative healthfulness of acandidate food serving. With reference to FIG. 10 , at the beginning ofa selected period, such as a day or a week, a variable SUM is set 20 to0. A consumer considers ingesting a candidate food serving and obtains24 data representing its identity and/or its nutrient content and apredetermined group including the candidate food serving. In order toevaluate the desirability of ingesting the candidate food serving, theconsumer obtains 26 food energy data and relative healthfulness data forthe candidate food serving based on at least one of the datarepresenting its (1) identity and (2) its nutrient content and groupclassification. Such food energy data and relative healthfulness isdetermined as disclosed hereinabove. In certain advantageousembodiments, such relative healthfulness is represented by distinctlydifferent and suggestive colors and/or shapes on packaging or labelingof a food product, for example: a green star to represent those foodsthat provided the greatest satiety for minimal kcal as well as anutritional profile which most closely complements public healthguidelines; a blue triangle to represent foods with a nutritionalprofile that is not as closely aligned with public healthrecommendations but does have satiety and nutritional virtues; a pinksquare to represent foods that provide minimal satiety or nutritionalvalue to overall intake but are likely to enhance the tastefulness orconvenience of eating; and a white circle to represent foods that, whilenot making much of a contribution to overall nutrition or feelings ofsatiety, provide pleasure and can be part of a healthy eating plan whenconsumed in moderation.

Based on the food energy data and relative healthfulness data thusobtained, the consumer determines whether to accept or reject 30 thecandidate food serving for consumption. For example, the consumer maywish to consume a snack food and must decide between a bag of fried cornchips and a bag of pocorn. He or she obtains their relativehealthfulness data using one of the processes disclosed hereinabove, anddecides 30 to select the popcorn because its healthfulness relative tothe fried corn chips is more favorable than that of the fried cornchips. Thus, if the consumer decides 30 to reject a candidate foodserving, the process returns to 24 to be repeated when the consumeragain considers a candidate food serving for ingestion.

If the consumer has decided that a candidate food serving issufficiently healthful or selected it in preference to another suchcandidate food serving, based on the obtained food energy data theconsumer decides 30 whether to ingest the candidate food serving or toreject it. If the value of SUM would exceed predetermined maximum dataif the consumer ingests the candidate food serving, the consumer decides30 to reject it and the process returns to 24 to be repeated when theconsumer again considers a candidate food serving for ingestion. If theconsumer decides to ingest the candidate food serving, the food energydata is added 32 to SUM, the consumer ingests 36 the candidate foodserving and the process returns to 24 to be repeated when the consumeragain considers a candidate food serving for ingestion. It will beappreciated that steps 32 and 36 need not be carried out in the orderillustrated. It will also be appreciated that the order in which theconsumer considers the healthfulness data and the food energy data canvary depending on personal preference.

Where the consumer considers two candidate food servings, and acceptsone to be ingested and rejects the other, in effect the process asillustrated in FIG. 10 is carried out twice, once for the candidate foodserving accepted by the consumer and again for the rejected candidatefood serving.

A method of selecting and purchasing food for consumption utilizing therelative healthfulness data and food energy data is illustrated in FIG.11 . When a consumer considers whether to purchase a given food offeredfor sale, the consumer supplies 250 data representing its identityand/or its nutrient content and a predetermined group including the foodoffered for sale. In order to evaluate the desirability of purchasingthe food, the consumer obtains 260 relative healthfulness data and foodenergy data for the food based on at least one of the data representingits (1) identity and (2) its nutrient content and group classification.The food may be a packaged food, such as a Weight Watcher® packaged foodthat displays an image on its packaging representing the relativehealthfulness data and food energy data of the product offered for sale.Instead it may be a packaged food that does not display such an image,so that the consumer inputs an identification of the packaged food, orelse its classification in a respective predetermined food group andnutrient content, in a device such as a PDA or cellular telephone toobtain a display of the relative healthfulness data, as disclose morefully hereinbelow. It might also be a food such as produce that isunpackaged and the consumer may obtain the relative healthfulness dataand food energy data in the same manner as for the packaged food lackingthe image representing same.

Based on the relative healthfulness data and the food energy data, theconsumer determines whether to accept or reject 270 the food forpurchase. For example, the consumer may wish to purchase cookies andwishes to decide between two competing brands of the same kind ofcookie. The relative healthfulness data and food energy data provide asimple and straightforward means of making this decision.

When the consumer has selected all of the foods to be purchased 280, heor she then purchases the selected foods 290 and delivers or has themdelivered 296 to his/her household for consumption.

FIG. 12 illustrates a data processing system 40 of certain embodimentsuseful in carrying out the processes of FIGS. 10 and 11 . The dataprocessing system 40 comprises a processor 44, a storage 50 coupled withthe processor 44, an input 56 coupled with processor 44, a presentationdevice 60 coupled with processor 44 and communications 64 coupled withprocessor 44.

Where system 40 is implemented as a PDA, laptop computer, desktopcomputer or cellular telephone, in certain ones of such embodiments theinput 56 comprises one or more of a keypad, a keyboard, apoint-and-click device (such as a mouse), a touchscreen, a microphone,switch(es), a removable storage or the like, and presentation device 60comprises an LCD display, a plasma display, a CRT display, a printer,lights, LED's or the like.

In certain ones of such embodiments, storage 50 stores data identifyingthe predetermined food groups and instructions for carrying out theprocesses necessary to produce the relative healthfulness data assummarized in equations (20) through (40) hereinabove. To obtain therelative healthfulness data, using input 56, the consumer inputs dataidentifying the food to be consumed or food offered for sale or anidentification of its predetermined food group, and processor 44retrieves appropriate instructions from storage 50 for carrying out therespective process for the identified food group. Storage 50 stores dataassociating food identity data with the corresponding food groups, sothat when the consumer inputs food identification data, processor 44accesses such data to identify its food group and then retrieves theappropriate processing instructions based thereon. Processor 44 thenprompts the consumer, via presentation device 60, to enter the relevantones of F_data, SF_data, DF_data, S_data, NA_data, M_serving, kcal DV,DD, and ED_data for a food to be purchased or candidate food servingdepending on the process to be carried out. Processor 44 then processesthe input data according to one of equations (20) through (40) toproduce the relative healthfulness data. Processor 44 then controlspresentation device 60 to display the relative healthfulness data to theconsumer.

In certain ones of such embodiments, storage 50 stores the necessaryweighting data and conversion factor data necessary to carry out one ormore of the processes summarized in equations (1) through (15)hereinabove to produce food energy data. Using input 56, the consumerinputs the data PRO, CHO and FAT, the data PROm, CHOm and FATm, or thedata PROm, Total_CHOm, DFm, Total_FATm, Sat_FATm, and ETOHm (asavailable), for a food or candidate food serving depending on theprocess to be carried out. Processor 44 retrieves the necessaryweighting data and conversion factor data, as need be, from storage 50and processes the input data according to one of equations (1) through(15) to produce the food energy data. Processor 44 then controlspresentation device 60 to display the food energy data to the consumer.

In certain ones of such embodiments, storage 50 stores relativehealthfulness data for a plurality of predetermined foods, which can beretrieved using an address based on an identification of the food inputby the consumer using input 56. Processor 44 produces an address for thecorresponding relative healthfulness data in storage 50 and reads therelative healthfulness data therefrom using the address. Processor 44then controls presentation device 60 to display the relativehealthfulness data to the consumer.

In certain ones of such embodiments, storage 50 stores food energy datafor a plurality of predetermined foods, which can be retrieved using anaddress based on an identification of the food input by the consumerusing input 56. Processor 44 produces an address for the correspondingfood energy data in storage 50 and reads the food energy data therefromusing the address. Processor 44 then controls presentation device 60 todisplay the food energy data to the consumer.

In certain ones of such embodiments, the relative healthfulness dataand/or the food energy data stored in storage 50 is downloaded from aserver via a network. With reference to FIG. 13 , in certain embodimentsa plurality of data processing systems 40′ and 40″, each correspondingto data processing system 40 access a server 76 via a network 70 toobtain the relative healthfulness data and/or the food energy data,either to obtain a database of such data or to update such a databasestored in their storage 50. Network 70 may be a LAN, WAN, metropolitanarea network or an internetwork, such as the Internet. Server 76 storesrelative healthfulness data and/or food energy data for a large numberand variety of foods and candidate food servings which have beenproduced thereby, obtained from another host on network 70 or adifferent network, or input from a removable storage device or via aninput of server 76.

In certain ones of such embodiments, processor 44 of one of dataprocessing systems 40′ and 40″ receives the input data from input 56 andthe consumer, and controls communications 64 to communicate such data toserver 76 via network 70. Server 76 either retrieves the correspondingrelative healthfulness data and/or the food energy data from a storagethereof (not shown for purposes of simplicity and clarity), or producesthe relative healthfulness data from the received data using the processidentified by the food group identification data and/or the food energydata, as appropriate, and communicates the produced data tocommunications 64. Processor 44 then controls presentation device 60 todisplay the received data to the consumer.

The systems of FIGS. 12 and 13 are configured in certain embodiments toproduce meal plan data for a person on request. A meal plan for a givenperson is based on a personal profile of the person and relativehealthfulness data and food energy data produced for a variety of foods,either prior to the request for the meal plan data or upon such request.The personal profile includes such data as may be necessary to retrieveor produce a meal plan tailored to the needs and/or desires of therequesting person, and can include data such as the person's weight,height, body fat, gender, age, attitude, physical activity level, weightgoals, race, religion, ethnicity, health restrictions and needs, such asdiseases and injuries, and consequent dietary restrictions and needs.This data is entered by the requesting person via input 56 of the system40 in FIG. 12 , and stored as a personal profile either by processor 44in storage 50, or communicated by communications 64 to be stored byserver 76.

In certain embodiments, processor 44 accesses appropriate instructionsfrom storage 50 to produce a plurality of meal plans each designed tofulfill predetermined criteria, such as a low-fat diet, a lowcarbohydrate diet, an ethnically or religiously appropriate diet, or thelike. Criteria and methods for producing such diets are well known andencompass the criteria and methods disclosed by US published patentapplication No. 2004/0171925, published Sep. 2, 2004 in the names ofDavid Kirchoff, et al. and assigned to the assignee of the presentapplication. US 2004/0171925 is hereby incorporated by reference hereinin its entirety.

Processor 44 also obtains healthfulness data and food energy dataproduced as described hereinabove for the various foods in or to beincluded in the meal plan data, and selects and/or substitutes foods forthe meal plan based on the healthfulness data and the food energy data.In certain ones of such embodiments, for a person attempting to losebody weight processor 44 selects and/or substitutes the foods based onthe food energy data in order to ensure that the person can achieve thedesired weight loss safely. In certain ones of such embodiments,processor 44 selects and/or substitutes the foods in order to maximizethe healthfulness of the foods in the meal plan data overall based ontheir relative healthfulness data. In certain ones of such embodiments,processor 44 selects and/or substitutes the foods in order to achieve aminimum target level of healthfulness of the foods in the meal plan databased on their relative healthfulness data. In certain ones of suchembodiments, the processor 44 produces meal plan data matched topredetermined criteria and stores the data in storage 50 for subsequentaccess upon a request for meal plan data. Upon receipt of such arequest, processor 44 accesses the meal plan data based on a requestersprofile data presents it to the requester via presentation device 60.

Once the meal plan data is been thus produced, processor 44 controlspresentation device 60 to present the meal plan data to the requestingperson. In certain embodiments in which the server 76 obtains the mealplan data, server 76 communicates the meal plan data to communications64 for presentation to the requesting person via presentation device 60.In certain ones of such embodiments, the server 76 produces meal plandata matched to predetermined criteria and stores the data forsubsequent access upon a request for meal plan data. Upon receipt ofsuch a request from one of systems 40′ and 40″, server 76 accesses themeal plan data based on a requester's profile data and communicates itto the requesting system for presentation to the requester.

Consumers often are confused by the extensive nutritional informationprinted on the packaging of foods. Some simply find it too burdensome toread such information, often in relatively fine print so that it can allfit in the available space, and then weigh the relative merits andundesirable aspects of such information. While the Traffic Light systemprovides a degree of simplification to this process, it is stillnecessary for the consumer to look for additional information on thepackaging in order to acquire information desired by those attempting tomaintain, lose or gain weight.

In certain embodiments, methods are provided for selecting and ingestingfoods in a way that enables the consumer to control body weight, whilesimplifying the task of evaluating the desirability of each of variousfoods based on multiple criteria. With reference to FIG. 14 , at thebeginning of a predetermined period, such as a day or a week, theconsumer or a data processing system sets 110 a variable “SUM” equal tozero.

When the consumer considers whether to ingest a candidate food serving,the consumer views 120 an integrated image including both a numeralrepresenting an energy value of the food serving and an auxiliary imagefeature representing a further nutritional quality of the food serving.In certain ones of such embodiments, the further nutritional qualitycomprises the relative healthfulness of the candidate food serving. Suchrelative healthfulness may be determined as disclosed in thisapplication, or in another manner. In certain advantageous embodiments,such relative healthfulness is represented by distinctly different andsuggestive image colors, shades, shapes, brightness, or textures. Incertain ones of such embodiments, the further nutritional qualityrepresents a relative heart healthiness of the candidate food serving,while in others it represents sugar content for use by diabeticconsumers. In certain ones of such embodiments, the further nutritionalquality represents an amount, presence or absence of a particularnutrient or nutrients. For example, body builders may wish to know theamount of protein in a serving of a particular candidate food serving orwhether such protein includes all essential amino acids.

The integrated image may be imprinted on the packaging or label of thecandidate food serving, or it may be displayed by a data processingsystem, such as a PDA, cellular telephone, laptop computer or desktopcomputer, as described more fully hereinbelow. It may also be displayedin a printed document.

The integrated image in certain embodiments comprises a numeralrepresenting the energy content of an associated food displayed on abackground colored to represent a further nutritional quality of thecandidate food serving. An example of such an integrated image isprovided in FIG. 15A wherein the numeral comprises an integer on a greenbackground with a triangular border. In certain advantageous embodimentsthe color green is used to represent a favorable nutritional qualityrelative to other candidate food servings in a predetermined food groupincluding the associated candidate food serving. For example, green mayrepresent those foods that provided the greatest satiety for minimalenergy content as well as a nutritional profile which most closelycomplements public health guidelines. The color blue may be used torepresent foods having a relatively lower healthfulness profile, such asfoods with a nutritional profile that is not as closely aligned withpublic health recommendations but does have satiety and nutritionalvirtues. The color pink may be used to represent foods with a relativelylower healthfulness profile than those coded blue, such as foods thatprovide minimal satiety or nutritional value to overall intake but arelikely to enhance the tastefulness or convenience of eating. The colorwhite may be used to represent foods falling within the lowesthealthfulness profile, such as foods that, while not making much of acontribution to overall nutrition or feelings of satiety, providepleasure and can be part of a healthy eating plan when consumed inmoderation.

A further example of such an integrated image is provided in FIG. 15Bwherein the numeral comprises a different integer within a circularborder. The shape of the border may be used by itself to representrelative healthfulness or another nutritional characteristic, while thenumeral represents food energy data. In other embodiments, both theshape of the border and a color, shading or texture enclosed by theborder can provide the data for the nutritional characteristicrepresented by the shape in FIG. 15B.

Still another example of an integrated image is provided in FIG. 15Cwherein the numeral 6.5 appears within the image to provide food energydata, and the rectangular border of the image, with or without a color,shading or texture code, to provide the data for the further nutritionalcharacteristic.

FIG. 15D illustrates a still further integrated image in which a numeralrepresenting an energy content of a candidate food serving is colored torepresent the further nutritional characteristic of the candidate foodserving. While the numeral of FIG. 15D is not enclosed within a border,in certain embodiments a border is provided. In still other embodiments,the numeral is shaded or textured to provide the data for the furthernutritional characteristic. Various other shapes may also be used, suchas a star, oval or donut shape. Any shapes, colors, textures andshadings may be used, whether alone or in combination to provide thedata for the additional nutritional characteristic. Moreover, arabicnumerals need not be used, so that any data representing numerical data(such as roman numerals) can serve as the numeral data to representenergy content.

With reference again to FIG. 14 , based on the data provided by theintegrated image, that is, the energy content data and the furthernutritional quality data provided thereby, the consumer determineswhether to accept or reject 130 the candidate food serving forconsumption. For example, the consumer may wish to consume a snack foodand must decide between a bag of fried corn chips and a bag of popcorn.He or she views the integrated image on each bag, and decides to consumethe popcorn both because its energy content and healthfulness relativeto the fried corn chips as revealed by the integrated image are morefavorable than those of the fried corn chips. The integrated image thusprovides an easily viewed and readily understood evaluation of multiplenutritional qualities of a candidate food serving.

In certain embodiments, with or without the use of a data processingsystem, the consumer adds the data represented by the numeral in theintegrated image associated with the candidate food serving to the SUM140, and if the SUM is less than a predetermined daily or weekly maximumMAX 150, the consumer ingests 160 the candidate food serving. In thealternative, the consumer first ingests the candidate food serving andthen adds the number data represented by the numeral in the integratedimage to SUM. For example, the consumer might not know the precise valueof SUM plus the number data, but is aware that it is relatively lowcompared to MAX.

A method of selecting and purchasing food for consumption utilizing theintegrated image is illustrated in FIG. 16 . When a consumer considerswhether to purchase a given food for consumption, the consumer views 310an integrated image associated with the food including both a numeralrepresenting an energy value of the food and an auxiliary image featurerepresenting a further nutritional quality of the food. The food may bea packaged food, such as a Weight Watchers® packaged food that displaysthe integrated image on its packaging. Instead it may be a packaged foodthat does not display such an image, so that the consumer inputs anidentification of the packaged food in a device such as a PDA orcellular telephone to obtain a display of the integrated image forevaluation, as disclose more fully hereinbelow. It might also be a foodsuch as produce that is unpackaged and the consumer may obtain anassociated integrated image in the same manner as for the packaged foodlacking the image.

Based on the data provided by the integrated image, that is, the energycontent data and the further nutritional quality data provided thereby,the consumer determines whether to accept or reject 320 the food forpurchase. For example, the consumer may wish to purchase cookies andwishes to decide between two competing brands of the same kind ofcookie. Each may have the same energy content, so that the consumer maywish to choose the brand having a more favorable healthfulness based ondiffering colors, shapes, textures, shadings or combinations thereofseen in the integrated image on each package. Or else if each has animage having the same auxiliary image feature, the consumer may wish toselect the brand having a lower energy content per serving.

When the consumer has selected all of the foods to be purchased 330, heor she then purchases the selected foods 340 and delivers or has themdelivered 350 to his/her household for consumption.

With reference again to FIG. 12 the data processing system 40illustrated therein is useful in certain embodiments for carrying outthe processes of FIGS. 14 and 16 . In certain ones of such embodiments,storage 50 stores (A) the weighting data and conversion factorsnecessary to carry out one or more of the processes summarized inequations (1) through (15) hereinabove to produce food energy data, and(B) data identifying the predetermined food groups and instructions forcarrying out the processes necessary to produce the relativehealthfulness data as summarized in equations (20) through (40)hereinabove.

For producing relative healthfulness data for the food to be consumed orthe food offered for sale, using input 56, the consumer inputs dataidentifying the food to be consumed or food offered for sale or anidentification of its predetermined food group, and processor 44retrieves appropriate instructions from storage 50 for carrying out therespective process for the identified food group. Storage 50 stores dataassociating food identity data with the corresponding food groups, sothat when the consumer inputs food identification data, processor 44accesses such data to identify its food group and then retrieves theappropriate processing instructions based thereon. Processor 44 thenprompts the consumer, via presentation device 60, to enter the relevantones of F_data, SF_data, DF_data, S_data, NA_data, M_serving, kcal DV,DD and ED_data for a food to be purchased or candidate food servingdepending on the process to be carried out. Processor 44 then processesthe input data according to one of equations (20) through (40) toproduce the relative healthfulness data.

For producing food energy data for the food to be consumed or the foodoffered for sale, using input 56, the consumer inputs appropriate data(as disclosed hereinabove), for a food or candidate food servingdepending on the process to be carried out. Processor 44 retrieves thenecessary weighting data and conversion factors, as need be, fromstorage 50 and processes the input data according to one of equations(1) through (15) to produce the food energy data.

Using the relative healthfulness data and food energy data thusproduced, processor 44 uses this data to retrieve an image dataset fromstorage 50 including data for producing the auxiliary image featurecorresponding to the healthfulness data and numeral data correspondingto the food energy data, and controls presentation device 60 to displayan integrated image based on the image dataset depicting the numeral andthe auxiliary image feature to convey the energy content and therelative healthfulness of the food offered for sale or to be consumed tothe consumer.

In certain ones of such embodiments, storage 50 stores relativehealthfulness data and food energy data for a plurality of predeterminedfoods, which can be retrieved using an address based on anidentification of the food input by the consumer using input 56.Processor 44 produces addresses for the corresponding relativehealthfulness data and food energy data in storage 50 and reads therelative healthfulness data and food energy data therefrom using theaddresses. Using the relative healthfulness data and food energy datathus produced, processor 44 uses this data to retrieve an image datasetfrom storage 50 including data for producing the auxiliary image featurecorresponding to the healthfulness data and numeral data correspondingto the food energy data, and controls presentation device 60 to displaythe integrated image.

In certain ones of such embodiments, storage 50 stores the imagedatasets for the integrated images for a plurality of predeterminedfoods, which can be retrieved using an address based on anidentification of the food input by the consumer using input 56. Basedon the food identification data input by the consumer using input 56,processor 44 produces an address corresponding to the input data andretrieves an image dataset from storage 50 corresponding thereto tocontrols presentation device 60 to display the integrated image for thefood thus identified.

In certain ones of such embodiments, the relative healthfulness data andfood energy data stored in storage 50 is downloaded from a server via anetwork. With reference again to FIG. 13 , a plurality of dataprocessing systems 40′ and 40″, each corresponding to data processingsystem 40 access a server 76 via a network 70 to obtain the relativehealthfulness data and food energy data, either to obtain a database ofrelative healthfulness data and food energy data or to update such adatabase stored in their storage 50. Network 70 may be a LAN, WAN,metropolitan area network or an internetwork, such as the Internet.Server 76 stores relative healthfulness data and food energy data for alarge number and variety of foods and candidate food servings which havebeen produced thereby, obtained from another host on network 70 or adifferent network, or input from a removable storage device or via aninput of server 76.

In certain ones of such embodiments, processor 44 of one of dataprocessing systems 40′ and 40″ receives the input data from input 56 andthe consumer, and controls communications 64 to communicate such data toserver 76 via network 70. Server 76 either retrieves the correspondingrelative healthfulness data and food energy data from a storage thereof(not shown for purposes of simplicity and clarity), or produces therelative healthfulness data and food energy data from the received datausing the process identified by the food group identification data and aselected one of the food energy data production processes, asappropriate, and communicates the relative healthfulness data and foodenergy data to communications 64. Processor 44 then retrieves thecorresponding image dataset from storage 50 and controls presentationdevice 60 to display the corresponding integrated image to the consumer.

In certain ones of such embodiments, processor 44 of one of dataprocessing systems 40′ and 40″ receives the input data from input 56 andthe consumer, and controls communications 64 to communicate such data toserver 76 via network 70. Server 76 retrieves a corresponding imagedataset for the corresponding integrated image and communicates it tocommunications 64. Processor 44 then uses the received image dataset tocontrol the presentation device 60 to display the integrated image tothe consumer.

FIG. 17 is a flow chart used to illustrate certain embodiments of aprocess for producing a food product having the integrated imageassociated therewith. A food product is obtained 400, whether byproducing the food product, by retrieving it from inventory or receivinga delivery thereof. Accordingly, the food product may be a processedfood product, or it may be a raw food product, such as an agriculturalproduct or seafood.

At least one of food identification data and food nutrient data of thefood product is supplied 410. The food identification data may be thename of the food, a stock keeping unit or other data as describedhereinbelow. In certain ones of such embodiments, food energy data forthe food product and further data representing a further nutritionalcharacteristic of the food product, such as relative healthfulness data,is obtained 420 based on the food identification data or the foodnutrient data, using one of the processes disclosed hereinabove.

In certain ones of such embodiments, the food identification data isinput to a data processing system storing food energy data and suchfurther data for one or more food products. In this example, the foodidentification data may be a name of the food product, an identifiersuch as a stock keeping unit, or data which associates the food productwith its respective stored food energy data. In certain ones of suchembodiments, such food nutrient data is supplied to a data processingsystem as may be required to produce food energy data and the furtherdata for the food product using one of the processes disclosedhereinabove. In certain ones of such embodiments, the data is obtainedfrom an appropriate record or calculated in accordance with one of theprocesses disclosed hereinabove.

Using the food energy data and the further data, a processor of the dataprocessing system retrieves an image dataset from a storage of the dataprocessing system including data for producing the auxiliary imagefeature corresponding to the further nutritional characteristic of thefood product, such as its relative healthfulness, and numerical datacorresponding to the food energy data, so that the integrated image maybe produced.

In certain ones of such embodiments, a storage of the data processingsystem stores image datasets corresponding to food identification dataand/or food nutrient data. The at least one of food identification dataand food nutrient data of the food product is used by a processor of thedata processing system to retrieve the image dataset from a storage ofthe data processing system.

In certain ones of such embodiments, the integrated image data isobtained for a known food product, with or without the use of a dataprocessing system. For example, the integrated image data may beobtained from publicly available packaging or labels, as data obtainedin electronic form via a network, such as the Internet or as dataobtained from other printed or electronically accessible sources.

The integrated image data obtained as disclosed hereinabove isassociated 430 with the food product. In certain ones of suchembodiments, the integrated image data is printed, applied or otherwisemade visible on packaging of the food product. In certain ones of suchembodiments, the integrated image data is made visible on a labelaffixed on or to the food product, such as an adhesive-backed label onproduce or a label tethered to a food product.

In certain embodiments, the food energy data and the relativehealthfulness data are associated with the food product in a form otherthan the integrated image, such as separately displayed data.

The foregoing disclosure of certain embodiments provides exemplary waysof implementing the principles of the present invention, and the scopeof the invention is not limited by this disclosure. This invention canbe embodied in many different forms and should not be construed aslimited to the embodiments set forth herein; rather, these embodimentsare provided so that this disclosure will be thorough and complete tothose skilled in the art. The scope of the present invention is insteaddefined by the following claims.

What is claimed is:
 1. A process for controlling body weight of aconsumer comprises, for each of a plurality of candidate food servings,receiving, by a processor, at least one of respective food servingidentification data and respective food serving nutrient data;obtaining, by the processor, respective food energy data representing anenergy content of each of the candidate food servings; determining, bythe processor, healthfulness data representing a relative healthfulnessof each of the candidate food servings, based on the respective foodserving identification data and the respective food serving nutrientdata; determining, by the processor, food servings for the plurality ofcandidate food servings based on the respective healthfulness data andthe respective food energy data such that a sum of respective foodenergy data of the selected food servings is in a predeterminedrelationship to a predetermined food energy benchmark for the consumerin a given period; and recommending, by the processor, the selected foodservings.
 2. The process of claim 1, wherein the respectivehealthfulness data for at least one of the candidate food servings isbased on (a) a selected respective procedure for processing nutritionaldata of foods in a respective food group comprising the at least one ofthe candidate food servings, the respective food group being one of aplurality of food groups of a respective metagroup of a plurality ofmetagroups, each of the metagroups comprising a plurality of food groupsand having a different respective procedure for processing thenutritional data of foods in the food groups within such metagroup, and(b) selected respective comparison data for the corresponding foodgroup, at least some of the food groups in each metagroup havingdifferent respective comparison data than the other food groups in suchmetagroup.
 3. The process of claim 1, wherein the respectivehealthfulness data representing a relative healthfulness of each of thecandidate food servings is based on a linear combination of selectednutrient amounts present therein.
 4. The process of claim 1, wherein therespective food energy data representing an energy content of each ofthe candidate food servings is based on a human being's metabolicefficiency in utilizing first and second nutrients therein as energy. 5.The process of claim 1, wherein the respective food energy datarepresenting an energy content of each of the candidate food servings isbased on an energy contribution of each of its protein content, itscarbohydrate content, its dietary fiber content and its fat content. 6.The process of claim 1, comprising obtaining meal plan data comprisingdata identifying candidate food servings to be ingested by the consumerover a given period based on the respective healthfulness data, therespective food energy data and the predetermined food energy benchmark,wherein the candidate food servings are ingested by the consumer inaccordance with the meal plan data.
 7. A process for selecting andpurchasing food comprises, using at least one of food identificationdata and food serving nutrient data of a food offered for sale,obtaining food energy data representing an energy content thereof andrelative healthfulness data representing a relative healthfulnessthereof; selecting the food offered for sale based on its food energydata and its relative healthfulness data; and purchasing the selectedfood offered for sale.
 8. The process of claim 7, wherein the relativehealthfulness data of the food offered for sale is based on (a) aselected respective procedure for processing nutritional data of foodsin a respective food group comprising the food offered for sale, therespective food group being one of a plurality of food groups of arespective metagroup of a plurality of metagroups, each of themetagroups comprising a plurality of food groups and having a differentrespective procedure for processing the nutritional data of foods in thefood groups within such metagroup, and (b) selected respectivecomparison data for the corresponding food group, at least some of thefood groups in each metagroup having different respective comparisondata than the other food groups in such metagroup.
 9. The process ofclaim 7, wherein the relative healthfulness data of the food offered forsale is based on a linear combination of selected nutrient amountspresent therein.
 10. The process of claim 7, wherein the food energydata representing an energy content of the food offered for sale isbased on a human being's metabolic efficiency in utilizing first andsecond nutrients therein as energy.
 11. The process of claim 7, whereinthe food energy data representing an energy content of the food offeredfor sale is based on an energy contribution of each of its proteincontent, its carbohydrate content, its dietary fiber content and its fatcontent.
 12. A process for providing data to a consumer to assist in aprocess for controlling the consumer's weight, comprising, receiving ina data processing system data provided by a consumer for a food servingselected by the consumer including at least one of food servingidentification data and food serving nutrient data; using a processor ofthe data processing system, obtaining food energy data and foodhealthfulness databased on the at least one of food servingidentification data and food serving nutrient data; and at least one of(a) communicating the food energy data and the food healthfulness datato a device for presentation to the consumer, and (b) presenting thefood energy data and the food healthfulness data to the consumer via apresentation device of the data processing system.
 13. The process ofclaim 12, wherein the food healthfulness data is based on (a) a selectedrespective procedure for processing nutritional data of foods in arespective food group comprising the food serving, the respective foodgroup being one of a plurality of food groups of a respective metagroupof a plurality of metagroups, each of the metagroups comprising aplurality of food groups and having a different respective procedure forprocessing the nutritional data of foods in the food groups within suchmetagroup, and (b) selected respective comparison data for thecorresponding food group, at least some of the food groups in eachmetagroup having different respective comparison data than other foodgroups in such metagroup.
 14. The process of claim 12, wherein the foodhealthfulness data is based on a linear combination of selected nutrientamounts present in the food serving.
 15. The process of claim 12,wherein the respective food energy data is based on a human being'smetabolic efficiency in utilizing first and second nutrients in the foodserving as energy.
 16. The process of claim 12, wherein the respectivefood energy data of the food serving is based on an energy contributionof each of its protein content, its carbohydrate content, its dietaryfiber content and its fat content.
 17. The process of claim 12,comprising receiving request data in the data processing systemcomprising food identification data for the food serving, using the foodidentification data to access data representing plurality of nutrientsof the food serving and processing the received data using the processorto produce at least one of the food energy data and the foodhealthfulness data for the food serving.
 18. The process of claim 12,comprising receiving request data in the data processing systemcomprising food identification data for the food serving, and using thefood identification data to access at least one of the foodhealthfulness data and the food energy data for the food serving.
 19. Asystem for providing data to a consumer to assist in a process forcontrolling the consumer's weight, comprising, an input operative toreceive data provided by a consumer for a food serving selected by theconsumer including at least one of food serving identification data andfood serving nutrient data; a processor coupled with the input toreceive the data provided by the consumer and configured to obtain foodenergy data and food healthfulness data based on the at least one offood serving identification data and food serving nutrient data; and atleast one of (a) communications coupled with the processor to receivethe food energy data and the food healthfulness data therefrom and tocommunicate the food energy data and the food healthfulness data to adevice for presentation to the consumer, and (b) a presentation devicecoupled with the processor to receive the food energy data and the foodhealthfulness data and operative to present the food energy data and thefood healthfulness data to the consumer.
 20. The system of claim 19,wherein the processor is configured to obtain the food healthfulnessdata based on (a) a selected respective procedure for processingnutritional data of foods in a respective food group comprising the foodserving, the respective food group being one of a plurality of foodgroups of a respective metagroup of a plurality of metagroups, each ofthe metagroups comprising a plurality of food groups and having adifferent respective procedure for processing the nutritional data offoods in the food groups within such metagroup, and (b) selectedrespective comparison data for the corresponding food group, at leastsome of the food groups in each metagroup having different respectivecomparison data than the other food groups in such metagroup.